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https://scidar.kg.ac.rs/handle/123456789/10832
Назив: | Studies on unfolding energy spectra of neutrons using maximum-likelihood expectation–maximization method |
Аутори: | Shahmohammadi Beni M. Krstic, Dragana Nikezic, Dragoslav YU, Kwan Ngok Peter |
Датум издавања: | 2019 |
Сажетак: | © 2019, China Science Publishing & Media Ltd. (Science Press), Shanghai Institute of Applied Physics, the Chinese Academy of Sciences, Chinese Nuclear Society and Springer Nature Singapore Pte Ltd. Energy spectra of neutrons are important for identification of unknown neutron sources and for determination of the equivalent dose. Although standard energy spectra of neutrons are available in some situations, e.g., for some radiotherapy treatment machines, they are unknown in other cases, e.g., for photoneutrons created in radiotherapy rooms and neutrons generated in nuclear reactors. In situations where neutron energy spectra need to be determined, unfolding the required neutron energy spectra using the Bonner sphere spectrometer (BSS) and nested neutron spectrometer (NNS) has been found promising. However, without any prior knowledge on the spectra, the unfolding process has remained a tedious task. In this work, a standalone numerical tool named “NRUunfold” was developed which could satisfactorily unfold neutron spectra for BSS or NNS, or any other systems using similar detection methodology. A generic and versatile algorithm based on maximum-likelihood expectation–maximization method was developed and benchmarked against the widely used STAY’SL algorithm which was based on the least squares method. The present method could output decent results in the absence of precisely calculated initial guess, although it was also remarked that employment of exceptionally bizarre initial spectra could lead to some unreasonable output spectra. The neutron count rates computed using the manufacturer’s response functions were used for sensitivity studies. The present NRUunfold code could be useful for neutron energy spectrum unfolding for BSS or NNS applications in the absence of a precisely calculated initial guess. |
URI: | https://scidar.kg.ac.rs/handle/123456789/10832 |
Тип: | article |
DOI: | 10.1007/s41365-019-0662-7 |
ISSN: | 1001-8042 |
SCOPUS: | 2-s2.0-85070463223 |
Налази се у колекцијама: | Faculty of Science, Kragujevac |
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